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Mojtaba Hadi Barhaghtalab is a robotics researcher whose work centers on the control and design of advanced robotic systems for rehabilitation and industrial applications. His primary research areas include sliding mode control, adaptive neuro-fuzzy systems, and robust control strategies for robotic manipulators and parallel robots. Barhaghtalab’s most cited paper, “Sliding mode control of an exoskeleton robot for use in upper-limb rehabilitation” (2015, 39 citations), presents the mechanical design and control of a 3-degree-of-freedom exoskeleton for post-stroke shoulder rehabilitation, demonstrating a direct impact on medical robotics. He further contributed to industrial robotics with “Dynamic analysis, simulation, and control of a 6-DOF IRB-120 robot manipulator using sliding mode control and boundary layer method” (2018, 32 citations), showcasing practical control solutions. His more recent work, “Design of an adaptive fuzzy-neural inference system-based control approach for robotic manipulators” (2023, 20 citations), highlights his ongoing innovation in intelligent control. Additionally, his 2016 study on robust neuro-adaptive controllers for cable-driven parallel robots (15 citations) underscores his expertise in handling complex, nonlinear systems. With over 100 total citations, Barhaghtalab’s contributions bridge theoretical control methods and real-world robotic applications, making him a notable figure in rehabilitation and industrial robotics.